Performance analyses of wastewater treatment plant : a case of Hazelmere water treatment plant

Abstract

There is still an existing gap in the assortment and treatment of domestic wastewater; where wastewater treatment plants exist, they frequently operate beneath a set of guidelines. This prompts the discharge of pollutants into natural water bodies, establishing an adverse consequence on the climate and on human wellbeing. The performance of wastewater treatment plants is a fundamental parameter to be observed and assessed. This allows for better comprehension of the plans and operating challenges in water treatment plants. The results from assessment evaluations might be used for strategic planning aimed at upgrading plant operations and promoting adjustment necessities for better plant output. In this study, the Hazelmere Wastewater Treatment System's performance was evaluated from 1999 to 2018. The study’s principal objective was to evaluate the exhibition of the treatment plant in terms of the expulsion of microbial and chemical contaminations. Secondary data from the plant’s data records were used in the analysis. The study was also aimed at developing a predictive model which can be used to estimate future trends and parameters. Since long-term forecasting may produce more variations and higher errors, the forecast is only made for the next three years. The analysis conducted by this study revealed that the Hazelmere wastewater treatment plant's performance met the predetermined criteria. The measured values of E. coli, turbidity, and iron were higher than the benchmark focus requirements established (recommended) by international standards. The expulsion of turbidity for the period under study all satisfied World Health Organization (WHO) and South African National Standards (SANS) for discharge [≤ 1 NTU]. Iron removal also satisfied the WHO/SANS standards for release at [≤2 mg/L]. From 1999 to 2018, the effluent produced by the wastewater treatment plant was pathogenfree, with a recorded annual average of 0MPN/100mL. As a result, E. coli removal efficiency was at 100% during the mentioned period. Given the cost of running the plant, it is crucial that enhancements are made to expand the plants performance. Potential enhancements must adhere to criteria such as low speculation and upkeep costs, an increase in the plant's water-driven limit, and being simple to work with and maintain. The findings revealed that the proposed stochastic model can accurately and consistently predict the concentrations of the plant's wastewater parameters. Hence, if consideration is given to the nature of the input factors of the model, stochastic demonstrating can be utilized to help support wastewater plants. This will lead to a reduction in the number of experiments performed to analyze the pollutants and thus minimizing plant operating costs.